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Seasonality of nitrogen balances in a Mediterranean climatewatershed, Oregon, US
Jiajia Lin . Jana E. Compton . Scott G. Leibowitz . George Mueller-Warrant .
William Matthews . Stephen H. Schoenholtz . Daniel M. Evans .
Rob A. Coulombe
Received: 31 May 2018 / Accepted: 4 December 2018 / Published online: 19 December 2018
� This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2018
Abstract We constructed a seasonal nitrogen
(N) budget for the year 2008 in the Calapooia River
Watershed (CRW), an agriculturally dominated tribu-
tary of the Willamette River (Oregon, U.S.) under
Mediterranean climate. Synthetic fertilizer application
to agricultural land (dominated by grass seed crops)
was the source of 90% of total N input to the CRW.
Over 70% of the stream N export occurred during the
wet winter, the primary time of fertilization and
precipitation, and the lowest export occurred in the dry
summer. Averaging across all 58 tributary subwater-
sheds, 19% of annual N inputs were exported by
streams, and 41% by crop harvest. Regression analysis
of seasonal stream export showed that winter fertil-
ization was associated with 60% of the spatial
variation in winter stream export, and this fertilizer
continued to affect N export in later seasons. Annual N
inputs were highly correlated with crop harvest N
(r2 = 0.98), however, seasonal dynamics in N inputs
and losses produced relatively low overall nitrogen
use efficiency (41%), suggesting that hydrologic
factors may constrain improvements in nutrient man-
agement. The peak stream N export during fall and
early winter creates challenges to reducing N losses to
groundwater and surface waters. Construction of a
seasonal N budget illustrated that the period of greatest
N loss is disconnected from the period of greatest crop
N uptake. Management practices that serve to reduce
the N remaining in the system at the end of the
growing season and prior to the fall and winter rains
should be explored to reduce stream N export.
Responsible Editor: Jack Brookshire.
Electronic supplementary material The online version ofthis article (https://doi.org/10.1007/s10533-018-0532-0) con-tains supplementary material, which is available to authorizedusers.
J. Lin (&)
National Research Council, National Academy of
Sciences, 200 SW 35th St, Corvallis, OR 97333, USA
e-mail: [email protected]
J. Lin � J. E. Compton � S. G. LeibowitzWestern Ecology Division, US EPA, 200 SW 35th St,
Corvallis, OR 97333, USA
J. E. Compton
e-mail: [email protected]
S. G. Leibowitz
e-mail: [email protected]
G. Mueller-Warrant
USDA ARS, National Forage Seed Production Research
Center, 3450 SW Campus Way, Corvallis, OR 97331,
USA
e-mail: [email protected]
W. Matthews
Oregon Department of Agriculture, Confined Animal
Feeding Operations, 635 Capitol St NE, Salem, OR, USA
e-mail: [email protected]
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Biogeochemistry (2019) 142:247–264
https://doi.org/10.1007/s10533-018-0532-0(0123456789().,-volV)(0123456789().,-volV)
Keywords Agriculture � GIS � Nutrient useefficiency � Grass seed crops � Seasonal analysis �Water quality � Nitrogen
Introduction
Production of food and energy required by rising
human populations has released large amounts of
nitrogen (N) to the environment over the past century
(Galloway et al. 2004). All forms of N other than N2
gas are defined as reactive N, which is produced
naturally by biological N-fixation and lightning and by
human activities, including cultivation of N-fixing
crops, fossil fuel combustion, and production of
fertilizers and munitions (Davidson et al. 2011).
Although the production and use of reactive N
supports human nutrition and well-being for a growing
global population, release of excess N beyond its
intended use has contributed to the degradation of air
quality, contamination of drinking water, hypoxia in
coastal waters, and emission of greenhouse gases to
the atmosphere (Sobota et al. 2015; Pennino et al.
2017; van Grinsven et al. 2013). While N release is a
global problem, much of the N released to the
environment occurs via local, non-point source path-
ways (Sobota et al. 2013). Developing the best
available information on N sources and loads in a
timely manner at the subwatershed scale is needed to
promote local, effective management of nitrogen
(Stoner 2011).
Budgets have been developed at different scales to
quantify reactive N sources and to examine drivers of
N release to the environment. Howarth et al. (1996)
estimated the total N flux to the North Atlantic Ocean
from 14 regions, and identified northeastern U.S. and
northwestern Europe watersheds as contributing the
largest N fluxes on a per unit area basis. They
identified sources of N within watersheds with high
human population density and a variety of land uses.
Many studies have examined annual N inputs and
outputs at regional scales and how they are affected by
human activities and watershed characteristics, for
example in the Illinois River Basin (David and Gentry
2000), the Sacramento-San Joaquin Valley of Cali-
fornia (Sobota et al. 2009), and the eastern US (Boyer
et al. 2002; Schaefer and Alber 2007). Goolsby et al.
(1999) assembled a comprehensive N budget for the
Mississippi River Basin that also included estimates
for N mineralization, immobilization, and denitrifica-
tion in soil, and N volatilization from crop canopies.
Annual N loss via stream flux has been shown to be a
function of net anthropogenic input (David and Gentry
2000; Howarth et al. 2012; McIsaac et al. 2002),
annual stream flow (Schaefer et al. 2009; Sobota et al.
2009), and changes in land use or nutrient manage-
ment (Hirsch et al. 2010). These studies establish the
foundations for predicting N loss on an annual basis
and for a range of anthropogenic sources.
Although large-scale, annual budgets are useful for
identifying drivers of inputs to regions or large coastal
areas like the Gulf of Mexico or the North Atlantic,
studies that incorporate data about local land use and
finer time steps are vital for informing local water
quality management. Studies comparing models
demonstrated that N budgets incorporating more detail
on N sources and land/water attenuation substantially
improve predictions of N export both at catchment
scales (Han and Allan 2008) and larger scales
(Alexander et al. 2002). High-resolution, locally
derived information on nutrient inputs to the landscape
from different sources can identify opportunities for
reducing N loading to sensitive surface waters and
groundwater systems (Luscz et al. 2015).
Many regional or smaller scale studies have been
carried out to understand watershed N balances in the
Midwestern, Southern, and Eastern US (Boyer et al.
2002; David et al. 1997; Schaefer et al. 2009). Studies
are needed to examine watershed N budgets in the
Pacific Northwestern US (PNW), in order to enhance
our knowledge of N management in the distinctive
Mediterranean climate of the PNW with wet winters
and dry summers. Hydrologic N export increases in
months with high precipitation, and generally is higher
S. H. Schoenholtz
Virginia Water Resources Research Center, Cheatham
Hall, Suite 210, Virginia Tech, 310 West Campus Drive,
Blacksburg, VA 24061, USA
e-mail: [email protected]
D. M. Evans
Center for the Environment, Plymouth State University,
Plymouth, NH 03264, USA
e-mail: [email protected]
R. A. Coulombe
CSS, 200 SW 35th St, Corvallis, OR 97333, USA
e-mail: [email protected]
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248 Biogeochemistry (2019) 142:247–264
in the wetter, west-side mountains of Oregon and
Washington than in other parts of the western US
(Kelley et al. 2013; Schaefer et al. 2009; Wise and
Johnson 2011). A number of TMDLs (Total Maximum
Daily Loads) have been developed in these states for
impaired waters that target nutrients as contributing
pollutants to violations of water quality standards
(USEPA 2018). In agricultural areas of central and
northwestern Washington and Oregon’s Willamette
Valley, groundwater nitrate concentrations often are
above the drinking water maximum contaminant level
of 10 mg NO3-N L-1 (Hoppe et al. 2011; Nolan and
Hitt 2006; Pennino et al. 2017). An examination of
inputs and exports at finer temporal and spatial scales
may improve our understanding of the drivers of these
high yields and concentrations, and in turn inform
water-quality management in regions with similar
climate and N-related water-quality problems.
The Calapooia River is a major tributary of the
Willamette River Basin in Oregon, previously iden-
tified as having high N concentrations relative to many
other Willamette tributaries (Bonn et al. 1996). Here
we apply the best available local and regional data to
assemble a comprehensive, seasonal N input–output
budget for the Calapooia River Watershed (CRW) in
2008. We chose 2008 because high resolution land
cover and input data coincided with stream chemistry
data for a network of 73 stream sampling locations in
the CRW. Quantified N inputs include agricultural,
industrial, human and animal waste, and natural
sources; exports include crop harvest and hydrologic
export. Objectives of the study were to (1) quantify
contributions of various N sources in the CRW and its
subwatersheds for the year 2008 using locally-derived,
crop-specific land-use information; (2) estimate frac-
tional N export via stream export and crop harvest; (3)
quantify the amount of N remaining in the watershed;
(4) study spatial and temporal variations in N inputs
and exports, and (5) explore dominant factors that
drive these variations. Previous work at the national
scale has shown that the spatial patterns of N export
are generally driven by inputs, but that climate factors
like precipitation dominate the temporal variability in
exports (Sinha and Michalak 2016). Our goal was to
use a high-resolution dataset derived from local crop
cover and fertilizer information to examine the relative
importance of both N inputs and hydrology in
affecting seasonal and annual N balances within the
watershed.
Methods
Study area
The Calapooia River is a major tributary of the
Willamette River, originating on the western slopes of
the Cascade Mountains of Oregon. Approximately
43% of the Calapooia River Watershed (CRW) is
occupied by evergreen forest (mostly short-rotation
industrial timber), mainly in the mountainous upper
watershed, and 53% is occupied by agricultural land,
predominantly grass seed crops in the flat valley floor
(Mueller-Warrant et al. 2011) (Fig. 1). The Calapooia
is a perennial stream with a mean discharge of
25 m3 s-1 and a watershed area of 963 km2 (Runyon
et al. 2004). Watershed elevation ranges from 56 to
1576 m. Precipitation occurs mostly from October to
May (Runyon et al. 2004), ranging
from\ 1000 mm year-1 at low elevations
to[ 2000 mm year-1 in the foothills of the mountain
range (Hoag et al. 2012). Soils are dominated by
Amity (Xeric Argialbolls) and Dayton (Vertic Alba-
qualfs) silt loam soil series in the valley and a variety
of Inceptisols in the mountainous areas (USDA 2017).
Among the 73 studied subwatersheds of the CRW that
represent the entire drainage upstream, 15 are main-
stream subwatersheds, and 58 are un-nested tributary
subwatersheds. The dominant land use of these
tributaries shifts from evergreen forest in the moun-
tainous area to cool-season grass seed crops on the flat
land (Fig. 1).
N input
Our goal was to assemble a comprehensive input–
output N budget for the CRW for 2008, the year that
we were able to gather the finest resolution, locally-
derived data on land use, N deposition, and CAFOs to
combine with stream chemistry data from the same
time period. 2008 is also a normal year with average
temperature and precipitation in a 10-year record
(2002–2012). Seven sources of N were examined: (1)
land application of agricultural fertilizer, (2) land
application of manure from concentrated animal
feeding operations (CAFOs), (3) atmospheric deposi-
tion, (4) biological N fixation (BNF) by crops, (5) BNF
associated with red alder trees (Alnus rubra), (6) non-
agricultural fertilizer applied to developed lands, and
(7) non-sewered septic waste (Table 1). We calculated
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Biogeochemistry (2019) 142:247–264 249
total N input from these seven sources at the water-
shed- and subwatershed levels (see SI for more
information). The total annual N input rate
(kg N ha-1 year-1) was calculated as the sum of all
7 inputs listed above scaled to the entire watershed or
subwatershed area in hectares (ha).
N outputs
Stream export
The US Geological Survey (USGS) Load Estimator
model (LOADEST; Runkel et al. 2004) was used to
simulate stream N load from 2002 to 2012 based on
stream chemistry data collected for 73 stream sam-
pling points within the CRW. The calibrated model
was then used to extract the N load results for the year
2008.
Surface water grab samples were collected and
analyzed for total nitrogen (TN) concentrations from
the 15 mainstream and 58 tributary stations in the
CRW from 2003 to 2006 (monthly or quarterly) by the
US Department of Agriculture (USDA) and Oregon
State University (OSU), and from 2009 to 2011
(quarterly) by the US Environmental Protection
Agency (EPA). The detection limit for the EPA
samples was 0.010 mg N L-1; the detection limit for
the USDA-ARS method was 0.04 mg N L-1 (Erway
et al. 2005; Evans 2007). See SI for detailed methods
for sample collection and analysis. A calibrated hybrid
hydrologic model, based in part on EXP-HYDRO
(Patil and Stieglitz 2014) and developed specifically
for the CRW, provided daily runoff estimates (in mm)
for streams to convert TN concentrations to loads (see
SI for more details).
The LOADEST simulation produced continuous
TN load output at a daily step, which was then
aggregated to calculate monthly, seasonal, and annual
stream export of TN at the Calapooia River main stem
and tributary sites. The simulation at each site was
Fig. 1 The Calapooia River
Watershed. Land use in
2008, modified based on
USDA-ARS map (Mueller-
Warrant et al. 2011). The flat
western lower portion of the
watershed is dominated by
agricultural land, and
mountainous eastern portion
by forestland
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250 Biogeochemistry (2019) 142:247–264
calibrated and evaluated using the Nash–Sutcliffe
coefficient (RNS2 ) and Load Bias in Percent (BP), a
coefficient that describes percent over/under estima-
tion of the observed load within the calibration data set
(USGS 2013). The RNS2 averaged 0.77 for all sites. The
calibrated absolute value of Bp averaged 6.4% for all
subwatersheds (see SI for details).
Crop harvest N removal
To calculate the N removal via crop harvest, we
combined information acquired from a crop N content
literature review with the 2008 land use map created
by USDA-ARS. The ARS land use map identified 30
types of major crops in the CRW. The total crop
removal of N was calculated as:
Ncrop;rmv ¼Xi
i¼1
Ai � Yi � 1� mið Þ � ni ð1Þ
where Ncrop;rmv is the total crop removal of N
(kg N ha-1 year-1) of the watershed; Ai and Yi are
respectively the planting area (ha) and yield
(kg ha-1 year-1) of crop i; mi is the moisture content
(%) of crop i, and ni is the N content (%) of crop i on a
dry weight basis. Planting area was based on the ARS
land use map. USDA National Agricultural Statistics
Service census data of 2007 and 2012 at the county
level were used to calculate crop yield for individual
fields, assuming crop yield is relatively constant. Crop
yield refers to the part of the crop removed from the
field during harvest. For example, in the study area,
most of the grass straw is baled and removed for export
during seed harvest. Therefore, N content in seed and
straw were calculated separately then added together
to estimate total N removal of grass seed crops. OSU
extension publications (see SI Table 1) and the online
USDA Crop Nutrient Tool (https://plants.usda.gov/
npk/main) were used to obtain the median crop
moisture and N content.
Table 1 Summary of watershed nitrogen inputs and data sources for the Calapooia River Watershed, Oregon USA
N Source Input
(kg N ha-1 year-1)
Percent of all
N inputs (%)
GIS data layer source and data year Resolution
Agricultural
fertilizer
80.0 90.0 USDA-ARSa (land use data, 2008); OSU extension
recommendations for crop fertilization rates (SI
Table 1)
30 m 9 30 m
Total
Atmospheric
deposition
4.9 5.4 CMAQb (2008) 4 km 9 4 km
Agricultural
BNFc2.3 2.5 USDA-ARSa (land use data, 2008) 30 m 9 30 m
Alder BNFc 1.4d 1.5 LEMMAe (2002) 30 m 9 30 m
Non-farm
fertilizer
0.2 0.2 USGS-SPARROWf (2002) 30 m 9 30 m
CAFOg manure 0.2 0.2 Oregon Department of Agriculture records (2008) 30 m 9 30 m
Non-sewered
population
0.1 0.1 USGS-SPARROWf (2002) 30 m 9 30 m
Total 89.0 100.0
aAgricultural Research ServicebCommunity Multiscale Air Quality Model (version 4.7.1) (Schwede and Lear 2014)cBiological Nitrogen FixationdRed alder fixation rate: 100 kg N ha-1 year-1, pure stand (chose lower range of 100-200 from Binkley et al. 1994, thus this is a
conservative estimate)eLandscape Ecology, Modeling, Mapping and Analysis (Ohmann et al. 2011)fSpatially Referenced Regressions on Watershed Attributes (Wise and Johnson 2013)gConfined Animal Feeding Operation derived manure applied to farmland
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Biogeochemistry (2019) 142:247–264 251
Surplus and remainder N
Surplus N (Nsur) is determined as the annual difference
between total N inputs and crop harvest removal of N
(Zhang et al. 2015), and represents the annual N inputs
minus crop harvest.
Nsur ¼X
Nin � Nharv ð2Þ
whereP
Nin is the sum of the N input rate from the
seven major N sources in the watershed (Table 1) and
Nharv is crop removal (Eq. 1). All terms are expressed
as kg N ha-1 year-1.
Remainder N was also estimated for the Calapooia
and its subwatersheds. We define remainder N (Nremn)
as the amount of annual N inputs remaining in the
watershed after removal via crop harvest and hydro-
logic export. It is calculated by subtracting total N
removal via harvest and stream export from the total
input on a per area basis:
Nremn ¼X
Nin � Nharv � Nstr ð3Þ
where Nstr is LOADEST derived stream export in
kg N ha-1 year-1. Possible fates of the remainder N
within the watershed include storage in fields in plant
perennial tissues or in soil, or elsewhere in the
watershed, e.g., in riparian zones. Remainder N could
also leach into groundwater or be lost from farm and
riparian soils in gaseous forms via denitrification and/
or volatilization.
Seasonal analyses
Linear regression analysis was conducted to investi-
gate factors associated with seasonal stream export of
N from agricultural tributary subwatersheds. Total N
input for each season, seasonal crop harvest removal
of N, and seasonal fertilizer input were used as initial
explanatory variables. Seasonal crop harvest removal
was calculated as the sum of all the crop harvest
occurring during that season in CRW. Seasonal
fertilizer input was the total amount of fertilizer
applied to all crop types based on crop N demand and
extension recommendations for that season; thus we
were able to account for additional fall fertilization to
some grass seed crops and split fertilization. This
analysis allowed us to break down the annual budget
into a finer scale and to characterize stream export of N
in each season.
To examine potential inter-seasonal interactions,
we added explanatory variables that represented net N
input accumulated respectively from the current
season alone, individual previous seasons, (NETWinter,
NETSpring, NETSummer, NETFall), and both current
and previous seasons (NETWinter?Spring, NET
Winter?Spring?Summer, NET Winter?Spring?Summer?Fall).
The ‘net’ seasonal terms allow us to study factors
controlling seasonal variation in N export and calculate
the legacy impact from preceding seasons. For exam-
ple, NETWinter?Spring?Summer is net N subject to stream
export at the end of summer after spring and winter
export and summer harvest. N removal
via winter harvest was considered as zero in our
analysis because there was no harvest between
January and March in the CRW. Therefore, NETWinter
?Spring?Summer was calculated as: [Total input of NWinter
?Spring?Summer] - [Stream exportWinter?Spring] - [Crop
removalSpring?Summer].
Results
Sources and rates of N inputs
Spatial distributions of N input rates across the CRW,
consisting of agricultural fertilizer, alder BNF, agri-
cultural BNF, total deposition, and non-farm fertilizer
are shown in Fig. 2. We included manure-derived N in
our total N input estimates, but did not map this input
to protect the identity of the small number of
individual CAFOs in the area. For the entire CRW,
annual N input rate was 89 kg N ha-1 year-1, with
90% of this input coming from agricultural fertilizer
(80 kg N ha-1 year-1, Table 1). Atmospheric depo-
sition was the second largest contributor, accounting
for 5% of total N input (5 kg N ha-1 year-1). Agri-
cultural BNF was the third largest input, with a rate of
2 kg N ha-1 year-1, followed by red alder BNF at a
rate of 1 kg N ha-1 year-1 across the entire water-
shed. Input of N from manure, non-farm fertilizer, and
septic systems accounted for a small portion in the
CRW, together accounting for\ 1 kg N ha-1 year-1
and\ 0.5% of inputs (Table 1). Input from non-
sewered septic waste was not plotted in Fig. 2 because
the contribution was negligible.
Substantial variability in N inputs was observed
across the watershed (Fig. 2). Among subwatersheds,
agricultural fertilizer input varied between 0 and
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252 Biogeochemistry (2019) 142:247–264
183 kg N ha-1 year-1. In the agriculturally domi-
nated subwatersheds, the contribution of fertilizer
input as a percentage of total N input ranged between
45 and 97%, and the total input rate ranged between 51
and 183 kg N ha-1 year-1. In the forested mountains,
N input was typically\ 10 kg N ha-1 year-1, with
atmospheric deposition and alder BNF being the two
main sources (Fig. 3). For intermediate slope subwa-
tersheds where Christmas trees and pasture are
intermixed with forestland, N inputs ranged between
15-30 kg N ha-1 year-1.
Outputs in streams and crop removal
Annual stream export of TN ranged from\ 1 to
57 kg N ha-1 year-1 among the 58 tributary subwa-
tersheds, with TN concentration ranging from\ 0.01
to 43 mg L-1 (Fig. 4); the highest rate of stream N
export occurred in the lower, agriculturally-dominated
part of the watershed. Annual export from mainstem
sections of the river generally increased downstream
and ranged from 2.1 to 25.9 kg N ha-1 year-1.
Stream N export was less than 5 kg N ha-1 year-1
on the forested portion of the CRW. For all the
tributary subwatersheds combined, annual stream
export of N in the CRW was 19% of total annual N
input, and 31% of annual surplus N.
N removed via crop harvest was\ 1 kg N ha-1 -
year-1 in forested watersheds overall (Fig. 5). Crop
harvest ranged widely from 6 to 75 kg N ha-1 year-1
on the agriculturally-dominated landscape, reflecting
variations in cover type within the watershed
(Fig. 6a). Annual crop removal was very strongly
correlated with total N inputs (r2 = 0.98, Fig. 5a).
Based on the regression slope, an average of 41% of
total N input was removed via crop harvest annually
among the 58 subwatersheds.
Fig. 2 Distribution of nitrogen (N) input rates to the Calapooia
River Watershed. Nitrogen sources are: agricultural fertilizer,
alder biological N fixation (BNF), agricultural BNF,
atmospheric N deposition, and non-farm fertilizer (the linear
features are roads in the watershed)
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Biogeochemistry (2019) 142:247–264 253
The ratio of harvest removal to stream export N
(DN), as an indicator of N Use Efficiency (NUE), is
closely related to land use and total input (Fig. 5d).DNgreater than 1 indicated crop harvest removed more N
than stream export. Subwatersheds dominated by
pasture land and some of the grass seed cropland had
higher DN values ([ 2). However, DN value was
approaching 1 for some intensively cultivated grass
seed crops. In general, DN increased with total N input
in the studied area until the total input exceeded
120 kg N ha-1 year-1, then DN started to decline
with enhancing input.
N balance remaining in the watershed
Annual surplus N (Nsur, Eq. 2) in the CRW ranged
from\ 0 to[ 150 kg N ha-1 year-1 (Fig. 7). Agri-
cultural subwatersheds were characterized by annual
surplus N values[ 50 kg N ha-1 year-1. Some but
not all of the highest surplus N areas were associated
with animal waste input. Most forested subwatersheds
were in a steady state with the annual surplus N
ranging between 0 and 15 kg N ha-1 year-1. The
exception was in areas where N-fixing alder trees were
Fig. 3 Annual input rates (a: kg N ha-1yr-1) and percent
contributions (b) of seven nitrogen (N) sources of the monitored
subwatersheds in the Calapooia River Watershed. Subwater-
sheds are oriented from lowest to highest percent agriculture
along the x-axis. Percent agricultural land ranges from 0
to\ 15% for subwatersheds defined as forestland, and from 15
to 93% for agricultural land
Fig. 4 Annual stream export of nitrogen for a Calapooia Riversubwatersheds (circles), and b Calapooia River mainstem sites
(triangles)
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254 Biogeochemistry (2019) 142:247–264
prevalent, resulting in N surplus estimates reaching
50 kg N ha-1 year-1 (Fig. 7).
Substantial variation in the amount of remainder N
(Eq. 3) was observed on agricultural subwatersheds,
ranging between 11 and 89 kg N ha-1 year-1, with a
mean of 53 kg N ha-1 year-1 (Fig. 5b and 6a). Based
on the regression slope, remainder N was similar in
magnitude to crop uptake, representing 40% of total N
input across the CRW (r2 = 0.87, Fig. 5b) and 69% of
annual surplus N (r2 = 0.90).
Seasonal N fluxes
Nitrogen inputs to the CRW varied strongly by season:
50% of nitrogen input occurred in the winter (usually
late February), 24% in the spring, 23% in the fall,
and\ 4% in the summer (Fig. 8a). These seasonal
proportions were driven by synthetic fertilizer input.
Atmospheric deposition was the second largest input
source of N in the CRW with highest deposition rates
occurring in summer and lowest in winter.
For the entire CRW, 71% of the watershed streamN
export occurred during winter months (peaked during
December and January), and very little stream N
export occurred in summer (\ 1%; Figs. 8b and 9).
The onset of winter stream export, however, occurred
prior to the period of largest fertilizer input in the
watershed. In the mountainous forested subwater-
sheds, 54% of stream N export occurred in winter,
24% in the fall, 20% of in spring and 2% in the
summer. In agricultural subwatersheds, mean stream
N export was respectively 64%, 30%, 6% and\ 1% in
winter, fall, spring and summer (Fig. 9). Winter was
the dominant season for hydrological export of N, but
there was also substantial stream export in both fall
and spring.
At the watershed scale, remainder N (Eq. 3) was
highest during winter (29 kg N ha-1), and lowest
during summer (- 24 kg N ha-1) (Fig. 8c). Approx-
imately 92% of N export via crop harvest happened in
summer, followed by spring (5%) and fall harvest
(3%) (Fig. 8b).
Fig. 5 Nitrogen
relationships in the
Calapooia River Watershed,
2008. a Annual crop
removal of nitrogen
(N) versus total N input.
b Remainder N versus total
N input. c Annual streamexport of N versus total N
input. d The ratio of crop
removal to stream export
(DN) versus total N input;
red dashed line: DN = 1.
The grey band in each
figure is the 95% confidence
level interval. Land use:
EVF evergreen forest, ITR
Italian rye grass, PRR
perennial rye grass, PST
pasture; RFR reforestation
and Christmas trees
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Biogeochemistry (2019) 142:247–264 255
Linear regression analysis of seasonal stream
export
The results demonstrated that there could be a time lag
between N input and hydrologic export. Winter
(January to March) fertilization exhibited a stronger
impact on fall stream N export (r2 = 0.66, p\ 0.0001)
rather than on spring and summer export (r2 values of
both are 0.38). Fall (October-December) inputs of
fertilizer did not explain much of the variability in fall
stream N exports. Legacy N from previous seasons
(winter and spring) and summer crop removal appear
to have a greater influence on fall stream export
(Table 2). Winter fertilization alone explained 60% of
the variation in winter stream N export. On average, an
equivalent of 24% of winter fertilizer was removed via
winter stream export.
Discussion
The mitigation of air and water quality issues caused
by N release to the environment relies upon quanti-
tative analysis of the source and fate of N, which can
be aided by constructing a comprehensive N budget.
Watershed budgets allow direct comparison among
watersheds in different regions, and enhance our
understanding of how land use and management
activities can alter nutrient fluxes and the environ-
mental consequences. Constructing a seasonal budget
can further improve our understanding on the timing
of nutrient losses and help establish better manage-
ment practices for the future. This work provides one
of the first seasonal, locally derived N input–output
budgets for a large mixed management watershed.
Comparison with other watersheds
As a predominantly agricultural watershed, the CRW
fertilizer input rate of 80 kg N ha-1 year-1, repre-
senting 90% of N inputs, was comparable to other US
watersheds (Boyer et al. 2002; Schaefer and Alber
2007; Sobota et al. 2009; Schaefer et al. 2009). Annual
fertilizer input among CRW subwatersheds ranged
from\ 1 to[ 180 kg N ha-1 year-1 in 2008, gener-
ally higher than fertilizer contributions in 22 previ-
ously studied watersheds on the west coast (\ 1 to
30 kg N ha-1 year-1; Schaefer et al. 2009). However,
the watersheds in Schaefer et al. (2009) had a lower
Fig. 6 Annual nitrogen harvest, stream export and remainder
rates (a: kg N ha-1yr-1) and percentages (b) in the subwater-
sheds of the Calapooia River Watershed. Subwatersheds are
oriented from lowest to highest percent agriculture along the
x-axis
Fig. 7 Annual surplus nitrogen (total input minus crop harvest
nitrogen) in the Calapooia River Watershed
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256 Biogeochemistry (2019) 142:247–264
percent agricultural land (\ 30%) compared to the
CRW (53% agriculture). The highest fertilizer rate
calculated for 21 California watersheds was approx-
imately 75 kg N ha-1 year-1 for the Salt/Mud Slough
Watershed with 74% agricultural land (Sobota et al.
2009), estimated based on inorganic N fertilizer
county-level sales data in 1991. According to a recent
USGS report on farm N usage, fertilizer application
rate in the same county had increased to
90 kg N ha-1 year-1 in 2008 (Brakebill & Gronberg
2017), similar to the 80 kg N ha-1 year-1 fertilizer
input rate in CRW.
Stream N export from CRW forested subwater-
sheds was less than 10 kg N ha-1 year-1 and aver-
aged 3 kg N ha-1 year-1, comparable to forested
watersheds in other studies (Boyer et al. 2002;
Schaefer and Alber 2007). However, regarding agri-
cultural subwatersheds, the CRW value (average of
22 kg N ha-1 year-1) was 1–2 times higher than in
other regions (Sobota et al. 2009; Boyer et al. 2002;
Schaefer and Alber 2007; Sigler et al. 2018). CRW
values are more similar to field-level nitrate leaching
fluxes of 24 kg N ha-1 year-1 from tile drained wheat
fields in eastern Washington (Kelley et al. (2013), and
N export of 18 kg N ha-1 year-1 in Montana agri-
cultural basins (Sigler et al. 2018). Upper Missouri
River basin watersheds of Montana also had a high
Fig. 8 a Seasonal nitrogen (N) input rates by source. b Seasonal N export rates via crop removal and stream flux. c Seasonal remainder
N in the Calapooia River Watershed. Negative remainder N rate in summer indicates a net seasonal N loss due to harvest
Fig. 9 Stream export of nitrogen in each season (a) and
seasonal export fraction (b) in the Calapooia River subwater-
sheds. Subwatersheds are oriented from lowest to highest
percent agriculture along the x-axis
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Biogeochemistry (2019) 142:247–264 257
proportion of fertilizer inputs exported (19–31% of
added fertilizer; Sigler et al. 2018), similar to the
CRW. The coincidence of late winter fertilization with
predominantly winter rains and wet or saturated soils
could be important drivers of the high N export rate
and proportion in the following seasons in parts of the
western US and other similar climates.
Table 2 Regression results of factors influencing annual and seasonal stream nitrogen (N) export in agricultural tributaries of the
Calapooia River Watershed (n = 37)
Explanatory variables Annual stream N export
(r2 and significance levelsa)
Seasonal stream N export (r2 and significance levelsa)
Winter Spring Summer Fall
Total seasonal N input
Spring 0.36*** na 0.24 0.27** 0.45***
Summer 0.13 na na ns ns
Fall 0.26* na na na 0.29**
Winter 0.63*** 0.60*** 0.39*** 0.39*** 0.66***
Seasonal N removal via harvest
Spring 0.02 na ns ns ns
Summer 0.62*** na na 0.35*** 0.67***
Fall 0.19* na na na ns
Winter na na na na na
Seasonal fertilizer N input
Spring 0.32** na 0.19 0.26 0.42***
Summer 0.02 na na ns ns
Fall 0.17 na na na 0.21
Winter 0.63*** 0.60*** 0.38*** 0.39*** 0.66***
NETWinterb na 0.60*** 0.39*** 0.39*** 0.66***
NETSpringc 0.35** na 0.23 0.25 0.45***
NETWinter ? Springd 0.39*** na 0.22 0.37*** 0.49***
NETSummere 0.59*** na na 0.34** 0.64***
NETWinter ? Spring ? Summerf 0.09 na na 0.33 0.19
NETFallg 0.32** na na na 0.35***
NETWinter ? Spring ? Summer ? Fallh 0.18* na na na 0.27**
Explanatory variables include total seasonal N input, seasonal harvest and fertilizer input, and accumulated ‘NET’ input from
previous seasons. Winter (January to March) is the first season in the analysis, and fall the last seasonaSignificance levels: ***p\ 0.0001, **p\ 0.001; number without ‘*’ sign: p\ 0.01, ns not significant, na analyses not carried out
because later season has no impact on earlier seasons in the yearbNETWinter = Winter surplus N = Total input of N (winter) - Crop removal (winter); because winter crop removal equals 0 in our
seasonal calculation, NETWinter is equal to total winter input of NcNETSpring = Spring surplus N = Total input of N (spring) - Crop removal (spring)dNETWinter ? Spring = Total input of N (winter ? spring) - Stream export (winter) - Crop removal (winter ? spring)eNETSummer = Summer surplus N = Total input of N (summer) - Crop removal (summer)fNETWinter ? Spring ? Summer = Total input of N (winter ? spring ? summer) - Stream export (winter ? spring) - Crop
removal (winter ? spring ? summer)gNETFall = Fall surplus N = Total input of N (fall) - Crop removal (fall)hNETWinter ? Spring ? Summer ? Fall = Total input of N (winter ? spring ? summer ? fall) - Stream export
(winter ? spring ? summer) - Crop removal (winter ? spring ? summer ? fall)
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258 Biogeochemistry (2019) 142:247–264
Remainder N averaged 53 kg N ha-1 year-1 for
agriculturally-dominated subwatersheds in CRW,
falling within the same range of estimates for some
California watersheds. Using published data from
Sobota et al. (2009), we estimated similar values for
remainder N in the Colusa (54% agricultural land) and
Upper San Joaquin River Basins (30% agricultural
land), respectively 42 kg N ha-1 year-1 and
55 kg N ha-1 year-1.
Impact of watershed management on nitrogen
export and balances
While both stream export and crop removal increased
with total N input, the relationship between these two
export paths was also a function of specific land use
types and input rates. As shown in Fig. 5d, the ratio of
harvest:stream N fluxes (DN) increases then decreaseswith N inputs. In evergreen forest subwatersheds,
stream export exceeded harvest removal since crop
harvest is minimal in these watersheds; we did not
have information about forest harvest, but wood
removal is expected to take little N off site. As N
inputs increase, crop harvest also increases leading to
a maximum DN of approximately 2:1. Then as total N
input continues to increase with higher fertilizer inputs
across the entire watershed, DN values diminished
drastically on several watersheds dominated by grass
seed fields. DN was close to 1 in these subwatersheds
where total input exceeded 150 kg N ha-1 year-1,
and the increase in N export via stream flow (as
indicated by the exponential trend in Fig. 5c) was
faster than the enhancement in crop uptake. As N
inputs continue to increase above 150 kg N ha-1
year-1, we start seeing a decline in ecosystem N
retention relative to stream export indicating a satu-
ration of uptake (e.g., Perakis et al. 2005). This
saturation could be related to timing of inputs. Like
many other grass seed crops, Italian ryegrass and
perennial ryegrass required additional fertilization in
fall to guarantee seed production. Even though fall
fertilizer was applied at a relatively small rate (around
45 kg N ha-1), it had a significant impact on N export.
A closer monitoring of crop growth and synchrony
between applied and soil available (mineralized)
nutrient supply and demand is necessary to reduce
hydrological loss of N in agricultural watersheds
(Arregui and Quemada 2008; Quemada et al. 2013).
Total annual stream export of N was well correlated
with winter fertilizer input (r2 = 0.63; Table 2), which
was the dominant source of annual N input to the
CRW. Annually, N loss to the CRW tributaries was
equivalent to 40% of fertilizer applied in the winter
months in the entire CRW. As shown in Fig. 9b,
agricultural subwatersheds had higher percentages of
seasonal stream export in winter but lower seasonal
stream export in spring compared to forested subwa-
tersheds. This shift in seasonality of stream export
could be attributed to winter fertilization to crop land.
The summer fraction of stream export was higher in
the forested, mountainous subwatersheds compared to
the flat agricultural land, presumably as a result of
summer runoff in the mountains that has been linked to
high elevation sources and snowmelt (Brooks et al.
2012). Denitrification accounted for only 0–6.8% of
stream nitrate moving through southern Willamette
Valley streams (Sobota et al. 2012), and thus we
assume that benthic denitrification is a relatively small
sink for N exported to streams.
The highest export in streams occurred in Decem-
ber to January, prior to the period of largest fertilizer
input in February through April. Nitrogen applied in
‘‘late winter’’ was by far the largest input, but these N
inputs were used by the growing crop, and not flushed
out until the next fall and winter. Seasonal input and
removal were relatively unimportant for spring stream
export (Table 2), indicating a portion of N entering
streams in the spring was a legacy from previous
seasons, originating from more unused or transformed
fertilizer N. Fall mineralization and mobilization of
organic matter from previous crops and late sum-
mer/fall tillage operations can generate additional
nitrate: Alva et al. (2002) found that cumulative N
mineralized in sandy soils could range between 72 to
172 kg N ha-1 during January through September on
PNW crop land with the highest mineralization
potential occurring in January. This may help explain
why winter was the highest stream export month even
though more fertilizer was applied late winter/early
spring on grass seed crops. Cumulative soil N from
previous growing seasons or years could also help
explain the net summer removal of N expressed as the
negative remainder N on Fig. 8c.
High net removal of N in summer did not prevent
high N loss to streams in fall. On the contrary, summer
harvest N removal was positively correlated with fall
stream export (r2 = 0.67). We also found a good
123
Biogeochemistry (2019) 142:247–264 259
correlation between fall stream export and NETSummer(r2 = 0.64), connecting high stream loss to intensive
cultivation that increased residual N accumulating
from previous seasons. The results suggested that
inorganic N accumulated in the soil during the dry
period after harvest removal, and crop growth in the
fall was too slow to capture all the N prior to leaching
loss. Furthermore, the drying and wetting cycles of
soil appear to facilitate fall stream export. Fall
precipitation recharged the dry soil and caused the
rise of groundwater level in the CRW (Conlon et al.
2005), perhaps moving the N out before it could be
taken up by the re-growing grass. As a result,
remobilized inorganic N could run off into intermittent
and ephemeral streams during fall and winter (Wig-
ington et al. 2003). We estimate that an equivalent of
10% of winter plus spring fertilizer (6 kg ha-1) was
exported via CRW streams in the following fall.
Temporal disconnects between N supply, move-
ment, and sinks within agricultural systems can result
in inefficiency in N use (Robertson and Vitousek
2009). Current crop management across the US is
tending toward more synchrony between crop demand
and supply of nutrients, to increase uptake efficiency
and reduce losses to the environment (Cassman et al.
2002). Possible practices designed to improve on-field
nutrient management include variable rate applica-
tions, split applications of fertilizer timed to crop
demand, incorporation of manure, irrigation water and
soil nitrate as additional sources of N, improvements
in irrigation practices, and use of nitrification
inhibitors (Ferguson 2015; Fernandez et al. 2016;
Lacey and Armstrong 2015). An interview study of
farmers across the US that included farmers in the
Calapooia Basin indicates that farmers generally did
not apply nutrient management plans, soil testing or
extension recommendations, but the study found
increased adoption of these practices when combined
with watershed education and funding for nutrient
management (Osmond et al. 2014). More communi-
cation and outreach may be needed for the increased
adoption and effectiveness of these practices in the
Willamette Valley.
Uncertainties in riparian buffers and tile drains
Use of cover crops and expansion of riparian buffers
have been widely proposed as means to reduce N
export to groundwater or streams (Dabney et al. 2010).
Some work calls into question riparian buffer expan-
sion as a significant mechanism for reducing hydro-
logic N loading to groundwater and streams in the
Willamette River Basin (Davis et al. 2008; Wigington
et al. 2005). For example, grass seed crops retained a
much higher proportion of added 15N than riparian
buffers: after 14 months, about 29–34% of added 15N
in perennial ryegrass systems in the CRW remained in
soils (0–30 cm), but only 12–17% remained in ripar-
ian soils (Davis et al. 2008). Lower N storage in
riparian soils was attributed to flooding and drying
events that reduced plant uptake and may have
increased the potential of N loss through overland
flow (Davis et al. 2006). Also, in the flat Willamette
Valley topography, N bypasses riparian zones by
moving from cropland into expanded stream networks
during large winter hydrologic events (Wigington
et al. 2005). Riparian zones have less impact on N
reduction when flow occurs across the surface and has
little interaction with plant roots and organic-rich
riparian soils. Hydrologic factors may result in a
bypassing of riparian buffers, constraining their ability
to remove N and reduce N export in the CRW.
Due to the lack of spatial information on tile
drainage, we currently are unable to incorporate the
effects of tile drain systems into the analysis. How-
ever, tile drainage could be a significant component of
N export in the CRW. While denitrification can occur
in tile drains when flow is slow during dry periods,
high concentrations of nitrate have also been found in
tile drains that intercept waters and bypass N removal
(Tesoriero et al. 2005). Kelley et al. (2013) found that
nitrification was the dominant N process in a tile-
drained field in Washington state, and there was no
evidence of denitrification at a large scale to influence
nitrate export. They also discovered the source of
nitrate in tile drain water shifted seasonally from
nitrified NH4? fertilizer during the high-discharge
period to mineralized soil organic N during the low-
discharge season (Kelley et al. 2013). This shifting N
transport dynamic in tile drains needs further
investigation.
Connections between seasonal balances
and annual nutrient use efficiency
For the entire US, agricultural N Use Efficiency
(NUE), calculated as N removed in crop harvest
divided by the sum of all N inputs, has ranged between
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260 Biogeochemistry (2019) 142:247–264
60-70% since the 1960s (Zhang et al. 2015). For the
CRW, mean NUE of crops was 41%, much lower than
the US national average. The estimated 41% removal
of N via crop harvest for the entire CRW is supported
by other local studies of grass seed crop N uptake.
A15N tracer study in the CRW found that 39% of15NH4 and 42% of 15NO3 were recovered in the
aboveground plant biomass of perennial ryegrass that
was fertilized in the winter (Davis et al. 2006). In
contrast, crop N uptake efficiency was 61% and 43%
for corn-soybean systems of Illinois and Iowa,
respectively (David et al. 1997; Keeney and DeLuca
1993). Thus, CRW rates of uptake by grass seed crops
appear to be at the lower range of those in the corn-
soybean systems of the Midwestern US. Crop and soil
factors may play a part in the differences in these NUE
rates. Another substantial difference between western
Oregon and the Illinois, where efficiencies were
higher, is the strong seasonality of precipitation in
the PNW (Hoag et al. 2012). Higher precipitation and
runoff during the winter appears to drive higher
seasonal N losses and lower NUE for crops in the
CRW as compared to many other areas in the US.
The disconnect between crop N requirements,
fertilizer applications and hydrologic N losses creates
challenges for N management in this area. Other
studies have shown that N leaching loss rates are
relatively high for many crops in the CRW area
(Selker and Rupp 2004; Young et al. 1997). Mueller-
Warrant et al. (2012) estimated that improvements to
fertilizer management in the CRW could reduce
hydrologic N export by approximately 24%, which
across the CRW would translate into a reduction in
stream N export of approximately 5.6 kg N ha-1 -
year-1. We determined that 71% of the hydrologic
export of N occurs during the early winter, which for
grass seed slightly precedes the primary time of
fertilizer application (mid-February to mid-March).
Split application of fertilizer did not reduce grass seed
yields (Young et al. 1997), suggesting that nutrient
management could be modified in this way to improve
water quality without sacrificing crop yields. Fall
fertilizer application is another practice that should be
carefully examined because much of the hydrologic
export of N occurs between late fall and early winter.
Development of nutrient best management practices
should consider year-round N leaching losses and
hydrologic export in order to better represent local soil
conditions, hydrology and the crop growth dynamic
and nutrient requirements.
Our novel analysis of seasonal input–output bal-
ances illustrates that watersheds with a Mediterranean
climate can experience significant loss in wet seasons
resulting in relatively low nutrient use efficiency.
These watersheds can have high N levels delivered to
ground and surface water under intensive agricultural
activities (De Paz et al. 2009; Piccini et al. 2016). In
order to reduce hydrologic N loss during wet winters, a
closer examination of fertilization practices is needed
to better match fertilizer inputs with crop growth and
uptake, thus minimizing surplus N in these
watersheds.
Acknowledgements We thank numerous farmers and other
private landowners for access to streams in the lower watershed,
and Robert Danehy of Weyerhaeuser Corporation for gaining
access to streams on their lands in the upper watershed. Donald
Streeter and Machelle Nelson, both formerly of USDA-ARS,
conducted lab and field work, and Randy Comeleo of US EPA
WED assisted with the spatial dataset. We also thank Blake
Hatteberg, Lindsey Webb, David Beugli, Howard Bruner, and
Marj Storm of CSS-Dynamac for stream sampling and data
collection in the Calapooia. We thank Ryan Hill for providing
support with spatial analysis using R and ArcGIS. Kara
Goodwin, Jackie Brenner, and Phil Caruso provided GIS
method development early in the project. The views expressed
in this paper are those of the authors and do not necessarily
reflect the views or policies of the United States Environmental
Protection Agency.
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